Papers
49
Total Citations
1,689
H-Index
21
About
Prahlad Vadakkepat is a distinguished robotics researcher whose work spans autonomous navigation, humanoid robotics, and human-robot interaction. Based at the National University of Singapore, he has made foundational contributions to intelligent robot control systems that bridge theoretical innovation and real-world application. His most influential work introduced the Evolutionary Artificial Potential Field (EAPF) methodology, which combines genetic algorithms with artificial potential fields to enable real-time robot path planning — a paper that has garnered over 344 citations and remains a landmark reference in autonomous navigation. Building on this, he extended EAPF principles to competitive robot soccer environments, demonstrating strong practical applicability. His research into fuzzy behavior-based architectures for mobile robots further advanced multi-agent coordination, while his work on Zero-Moment-Point compensation and genetic algorithm-optimized bipedal gaits has meaningfully advanced humanoid locomotion stability. Vadakkepat also contributed significantly to human-robot interaction, developing multimodal face detection and tracking systems essential for robots operating in dynamic social environments. His editorial work on *Humanoid Robotics: A Reference* (2017–2018) reflects his role as a synthesizer of the field. With over 1,200 cumulative citations across his top works, his research continues to shape the development of intelligent, socially aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Multimodal Approach to Human-Face Detection and Tracking177 citations · 2008
- 3Humanoid Robotics: A Reference124 citations · 2018
- 4Humanoid Robotics: A Reference99 citations · 2017
- 5Fuzzy Behavior-Based Control of Mobile Robots96 citations · 2004
- 6
- 7Disturbance rejection by online ZMP compensation66 citations · 2007
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- 10